[Kernel] Add weightless RMSNorm CUDA kernels for has_weight=False (#41430)

[hello-args]

RMSNorm(has_weight=False) (FlashNorm-folded checkpoints, #40117) only skipped the per-channel multiply on the native path. The CUDA/CPU _C kernels required a weight tensor, so the layer substituted an all-ones tensor and ran the weighted kernel — correct, but a wasted load + multiply. Fixes #41430.

This makes weight optional on the existing rms_norm / fused_add_rms_norm ops and templates the kernels on HasWeight, rather than adding separate *_weightless ops. The weighted hot path is unchanged.

Changes

• csrc/{libtorch_stable,cpu}: rms_norm / fused_add_rms_norm take Tensor? weight; kernels templated on bool HasWeight to skip the multiply when weight is null.
• layernorm.py: pass weight=None when has_weight=False; removes the old heuristic that guessed whether the native impl would be dispatched ([RFC][vLLM IR] rms_norm weight passing inconsistency #39370).
• vllm_c.py / xpu_ops.py: drop the ones-substitution; XPU falls back to native (the weightless _C path is CUDA/ROCm only).
• _custom_ops.py: weight: Tensor | None.
• test_layernorm.py: test_rms_norm_weightless vs forward_native, plus opcheck with weight=None.

Backends that require a weight (e.g. oink) fall back via IR op priority. Companion loader for FlashNorm-folded Llama checkpoints: #41431.

Test

pytest tests/kernels/core/test_layernorm.py -v   # requires a CUDA source build

Developed with AI assistance (Claude); all changed lines human-reviewed.

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[hello-args]

Update:

I investigated the Intel CI failure and pushed a follow-up fix.

The issue was that the new weightless RMSNorm custom ops are CUDA-only. XPU dispatch was incorrectly attempting to call those ops when weight=None, causing the IR test failure.

The fix falls back to the existing native IR implementation on XPU for weight=None, while preserving the new weightless CUDA kernel path unchanged.

The remaining test_audio_in_video failures appear unrelated to this PR (Qwen2.5-Omni multimodal/server tests).

Please let me know if you'd like additional benchmarks or validation.

[AndreasKaratzas]

Looks clean, the part that I can stamp is the test though.

[AndreasKaratzas]

Tolerance is a bit high, I see that the "weighted" test has the exact same tolerance (which is something that we should probably fix in a different PR) but did you try lower tolerance or generally do you have any error analysis over let's say 10 looped runs?

[hello-args]

Thanks for the review!

I matched the tolerance used in the existing weighted RMSNorm tests for consistency. I'll be running additional validation on an A100 and will share the error analysis/results shortly to see if we can safely tighten it.

[mergify]

This pull request has merge conflicts that must be resolved before it can be
merged. Please rebase the PR, @hello-args.

https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/syncing-a-fork

[hello-args]

Thanks for the suggestion, I've pushed a refactor based on the feedback.

Changes:

1. Removed the separate rms_norm_weightless / fused_add_rms_norm_weightless ops and dispatch paths.
2. rms_norm / fused_add_rms_norm now accept Tensor? weight; when has_weight=False we pass nullptr and skip the per-channel multiply.
3. Dispatches to HasWeight=true/false specializations internally, so the weighted path stays branch-free without adding new public _C ops.
4. Dropped the benchmark and error-analysis scripts.
5. Kept the correctness coverage (test_rms_norm_weightless + opcheck with weight=None).

Net result is the same optimization with a smaller surface area and no new operators.

Could someone add the ready label so the full CI can run?

Let me know if you'd like any further cleanup.

cc @mgoin @ProExpertProg @AndreasKaratzas @tjtanaa

[mgoin]

LGTM, thanks for simplifying

[mergify]

Hi @hello-args, the pre-commit checks have failed. Please run:

uv pip install pre-commit>=4.5.1
pre-commit install
pre-commit run --all-files

Then, commit the changes and push to your branch.

For future commits, pre-commit will run automatically on changed files before each commit.

[hello-args]

Thanks @mgoin!

I took a look through the failed jobs and they seem unrelated to the RMSNorm changes here:

• NIXL jobs are failing because nixl_ep_cpp isn't present in the test environment.
• Cudagraph is hitting a GPU memory cleanup timeout.
• Distributed DP tests are failing because servers aren't starting in time.
• Plugin tests are failing in the scheduler plugin suite.
• Spec decode is failing during engine initialization.

The RMSNorm/kernel correctness tests relevant to this change passed. Happy to dig deeper if you think any of these could be connected to this PR.